4.8 Article

Fluorescence and SEM correlative microscopy for nanomanipulation of subcellular structures

期刊

LIGHT-SCIENCE & APPLICATIONS
卷 3, 期 -, 页码 -

出版社

SPRINGERNATURE
DOI: 10.1038/lsa.2014.105

关键词

correlative microscopy; fluorescence; image correlation; nanomanipulation; SEM; subcellular structures

类别

资金

  1. Canadian Institutes of Health Research via a Catalyst Grant
  2. Canada Research Chairs Program
  3. Ontario Research Funds-Research Excellence Program
  4. Natural Sciences and Engineering Research Council of Canada via a Strategic Projects Grant

向作者/读者索取更多资源

Nanomanipulation under scanning electron microscopy (SEM) enables direct interactions of a tool with a sample. We recently developed a nanomanipulation technique for the extraction and identification of DNA contained within sub-nuclear locations of a single cell nucleus. In nanomanipulation of sub-cellular structures, a key step is to identify targets of interest through correlating fluorescence and SEM images. The DNA extraction task must be conducted with low accelerating voltages resulting in low imaging resolutions. This is imposed by the necessity of preserving the biochemical integrity of the sample. Such poor imaging conditions make the identification of nanometer-sized fiducial marks difficult. This paper presents an affine scale-invariant feature transform (ASIFT) based method for correlating SEM images and fluorescence microscopy images. The performance of the image correlation approach under different noise levels and imaging magnifications was quantitatively evaluated. The optimal mean absolute error (MAE) of correlation results is 68 +/- 34 nm under standard conditions. Compared with manual correlation by skilled operators, the automated correlation approach demonstrates a speed that is higher by an order of magnitude. With the SEM-fluorescence image correlation approach, targeted DNA was successfully extracted via nanomanipulation under SEM conditions.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Biophysics

1H, 13C, and 15N resonance assignments of reduced apo-WhiB4 from Mycobacterium tuberculosis

Qiran Zhai, Chen Lin, Bo Duan, Jun Liu, Lu Zhang, Bin Xia

Summary: WhiB4 protein, a member of the WhiB-like protein family, plays a crucial role in the survival and pathology of Mycobacterium tuberculosis. Acting as a transcription factor, WhiB4 regulates genes involved in redox balance, central metabolism, and respiration. It exists in different forms under different redox environments, including a dimeric holo form with iron-sulfur cluster, multimeric disulfide-linked oxidized apo forms, and a monomeric reduced apo form.

BIOMOLECULAR NMR ASSIGNMENTS (2021)

Article Multidisciplinary Sciences

Structure of mycobacterial ATP synthase bound to the tuberculosis drug bedaquiline

Hui Guo, Gautier M. Courbon, Stephanie A. Bueler, Juntao Mai, Jun Liu, John L. Rubinstein

Summary: The study of the ATP synthase structures in Mycobacterium smegmatis has provided insights into how the enzyme conserves energy through autoinhibition of ATP hydrolysis and the mechanism of action of the drug bedaquiline used in treating multidrug-resistant tuberculosis. Tuberculosis, caused by Mycobacterium tuberculosis, is increasingly resistant to first-line antibiotics, allowing infections to remain dormant and decreasing susceptibility to many antibiotics. Bedaquiline, developed from a lead compound identified in a screen against Mycobacterium smegmatis, targets the mycobacterial ATP synthase and is a cornerstone in the treatment of multidrug-resistant and extensively drug-resistant tuberculosis.

NATURE (2021)

Letter Cardiac & Cardiovascular Systems

REPLY FROM AUTHORS: ANATOMICAL OR FUNCTIONAL REPAIR FOR ISCHEMIC MITRAL REGURGITATION: FIND THE RIGHT ANTIDOTE!

Song Wan, Jia Hu, Jun Liu

JOURNAL OF THORACIC AND CARDIOVASCULAR SURGERY (2022)

Review Biochemistry & Molecular Biology

Xenogeneic Silencing and Bacterial Genome Evolution: Mechanisms for DNA Recognition Imply Multifaceted Roles of Xenogeneic Silencers

Bo Duan, Pengfei Ding, William Wiley Navarre, Jun Liu, Bin Xia

Summary: Horizontal gene transfer (HGT) is a major driving force for bacterial evolution, with xenogeneic silencers playing a crucial role in recognizing and suppressing foreign genes to maintain genomic stability. The diversity in DNA recognition mechanisms of xenogeneic silencers leads to clear characteristics in DNA sequence preferences, correlated with different host genomic features. Xenogeneic silencers also act as a selective force against GC to AT mutational bias in bacterial genomes and help maintain host genomic AT contents at relatively low levels.

MOLECULAR BIOLOGY AND EVOLUTION (2021)

Article Engineering, Electrical & Electronic

TrajectoryCNN: A New Spatio-Temporal Feature Learning Network for Human Motion Prediction

Xiaoli Liu, Jianqin Yin, Jin Liu, Pengxiang Ding, Jun Liu, Huaping Liu

Summary: The paper introduces a new end-to-end feedforward network, TrajectoryCNN, for predicting future human poses by capturing motion dynamics with coupled spatio-temporal features, dynamic local-global features, and global temporal co-occurrence features. The method achieves state-of-the-art performance on five benchmarks, demonstrating its effectiveness in human motion prediction.

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2021)

Article Chemistry, Multidisciplinary

Automatic Microscopy Analysis with Transfer Learning for Classification of Human Sperm

Rui Liu, Mingmei Wang, Min Wang, Jianqin Yin, Yixuan Yuan, Jun Liu

Summary: Infertility is a global issue impacting many couples, with sperm morphology being a crucial indicator of fertility. Manual classification of sperm by medical experts is labor-intensive and reliant on their experience. By leveraging a transfer learning method based on AlexNet, automatic classification of sperm into WHO-standard categories can achieve high accuracy and precision, showing promise for future applications.

APPLIED SCIENCES-BASEL (2021)

Article Computer Science, Artificial Intelligence

Sign Language Recognition Based on R(2+1)D With Spatial-Temporal-Channel Attention

Xiangzu Han, Fei Lu, Jianqin Yin, Guohui Tian, Jun Liu

Summary: In this study, a deep R(2+1)D model was adopted for sign language recognition, which improved the optimization process by separating spatial and temporal modeling. Additionally, a lightweight spatial-temporal-channel attention module was proposed to concentrate the network on significant information. Experimental results demonstrated the effectiveness of the proposed method, achieving superior or comparable results to state-of-the-art methods.

IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS (2022)

Article Computer Science, Interdisciplinary Applications

AIMIC: Deep Learning for Microscopic Image Classification

Rui Liu, Wei Dai, Tianyi Wu, Min Wang, Song Wan, Jun Liu

Summary: This study developed a software named AIMIC that allows users to apply deep learning technology for microscopic image classification without coding. In evaluation experiments, ResNeXt-50-32 x4d outperformed other algorithms, while MobileNet-V2 achieved a good balance between performance and computational cost.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2022)

Article Robotics

Versatile Motion Generation of Magnetic Origam Spring Robots in the Uniform Magnetic Field

Sishen Yuan, Sifan Cao, Junnan Xue, Shijian Su, Junyan Yan, Min Wang, Wenchao Yue, Shing Shin Cheng, Jun Liu, Jiaole Wang, Shuang Song, Max Q-H Meng, Hongliang Ren

Summary: This study investigates the motion generation and control of an untethered magnetic flexible robot with a stretch-twist coupling origami spring skeleton, using uniform magnetic field control. The robot can perform various motions under two-dimensional magnetic signal inputs, including in-plane crawling and axial rolling motion.

IEEE ROBOTICS AND AUTOMATION LETTERS (2022)

Review Engineering, Multidisciplinary

Selective and Independent Control of Microrobots in a Magnetic Field: A Review

Min Wang, Tianyi Wu, Rui Liu, Zhuoran Zhang, Jun Liu

Summary: This paper reviews recent advances in selective and independent control for multi-microrobot or multi-joint microrobot systems driven by magnetic fields. It introduces methods to decode global magnetic fields for individualized actuation of multiple microrobots and emphasizes the importance of independent control for the effective cooperation of multiple microrobots in accomplishing complex operations.

ENGINEERING (2023)

Article Engineering, Electrical & Electronic

Liquid Metal-Based Flexible Sensor for Perception of Force Magnitude, Location, and Contacting Orientation

Min Wang, Jingjing Zhang, Ruomao Liu, Tianyi Wu, Wei Dai, Rui Liu, Jiachen Zhang, Jun Liu

Summary: Flexible sensors have the advantage of enabling intelligent systems to interact with the environment safely and without limitations. This article proposes a novel method for simultaneously sensing force magnitude and contact location using liquid metal electrodes. The proposed multifunctional sensing device demonstrates high accuracy and wide sensing range, making it suitable for human-machine interactions and industrial applications.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2023)

Proceedings Paper Automation & Control Systems

On-Chip Transportation and Mixing of Microsample Using Electrohydrodynamic Flow

Min Wang, Zicheng Li, Wei Dai, Rui Liu, Sishen Yuan, Jun Liu

Summary: Microfluidic devices and lab-on-a-chip systems are widely used in biological and biomedical applications. This study focuses on developing a novel flow governing device for active sample transportation and assembly using electrohydrodynamic force. Experimental results confirm the effectiveness of the proposed system in transporting and assembling samples.

PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON MANIPULATION, AUTOMATION, AND ROBOTICS AT SMALL SCALES (MARSS 2022) (2022)

Proceedings Paper Automation & Control Systems

Dynamic tracking for microrobot with active magnetic sensor array

Min Wang, Kwan Yi Leung, Rui Liu, Shuang Song, Yixuan Yuan, Jianqin Yin, Max Q-H Meng, Jun Liu

Summary: This paper presents a new dynamic tracking solution for medical microrobotics by using a movable sensor array to optimize the range and accuracy of magnetic tracking. A multi-point locating algorithm is proposed to minimize background noise, showing significant potential to improve position feedback in medical applications.

2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021) (2021)

Proceedings Paper Automation & Control Systems

Neighborhood Spatial Aggregation based Efficient Uncertainty Estimation for Point Cloud Semantic Segmentation

Chao Qi, Jianqin Yin, Huaping Liu, Jun Liu

Summary: This paper proposes a method called NSA-MC dropout for efficient uncertainty estimation in point cloud semantic segmentation, which achieves uncertainty estimation through one-time inference and outperforms traditional MC dropout in terms of efficiency and impact on semantic inference.

2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021) (2021)

Article Engineering, Electrical & Electronic

Multipoint Simultaneous Tracking of Wireless Capsule Endoscope Using Magnetic Sensor Array

Min Wang, Shuang Song, Jun Liu, Max Q. -H. Meng

Summary: This study proposed a method for simultaneous localization using magnetic density of sampling points to offset background noise field, achieving multipoint simultaneous positioning. The robustness of the proposed method in different environments was verified through simulation and experimental analysis.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2021)

暂无数据